[Abstract unavailable

Compared with model architectures, the training process, which is also crucial to the success of detectors, has received relatively less attention in object detection. In this work, we carefully revisit the standard training practice of detectors, and find that the detection performance is often limited by the imbalance during the training process, which generally consists in three levels -sample level, feature level, and objective level. To mitigate the adverse effects caused thereby, we propose Libra R-CNN, a simple but effective framework towards balanced learning for object detection. It integrates three novel components: IoU-balanced sampling, balanced feature pyramid, and balanced L1 loss, respectively for reducing the imbalance at sample, feature, and objective level. Benefitted from the overall balanced design, Libra R-CNN significantly improves the detection performance. Without bells and whistles, it achieves 2.5 points and 2.0 points higher Average Precision (AP) than FPN Faster R-CNN and RetinaNet respectively on MSCOCO.

The ramp lesion is a common meniscal injury that can occur at the time of anterior cruciate ligament rupture or as a result of knee laxity associated with anterior cruciate ligament insufficiency. The prevalence of ramp lesion in this patient group was 16.6%, which increased with time until 24 months after initial injury. Patients younger than 30 years of age and male patients had a higher prevalence of ramp lesions.

This short-term study showed that, in terms of stability, synovial coverage, and proprioception recovery, remnant preservation ACLR using an allograft had no evident advantages in clinical outcome over the standard technique.

This prospective randomized controlled trial showed that, in terms of subjective scores, knee stability, and meniscal healing status, concomitant stable ramp lesions of the medial meniscus treated with abrasion and trephination alone during ACL reconstruction resulted in similar clinical outcomes compared with those treated with surgical repair.

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An ultrathin cantilever based on nanoorganized film from six alternating monolayers of clay plates, polycations, and magnetite nanoparticles was developed. The 170-nm thick clay−polymer−magnetite cantilever is a magnetic free-standing microstrip with a root anchored on a substrate. Hundreds of such cantilevers can be produced on a solid substrate within one processing cycle and, therefore, to provide sensor arrays or an adjustable surface with synchronized cantilever movements using an external magnetic field.